HyukjinKwon commented on a change in pull request #32926:
URL: https://github.com/apache/spark/pull/32926#discussion_r652406420
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File path: python/docs/source/development/ps_design.rst
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@@ -1,85 +0,0 @@
-=================
-Design Principles
-=================
-
-.. currentmodule:: pyspark.pandas
-
-This section outlines design principles guiding the pandas API on Spark.
-
-Be Pythonic
------------
-
-Pandas API on Spark targets Python data scientists. We want to stick to the
convention that users are already familiar with as much as possible. Here are
some examples:
-
-- Function names and parameters use snake_case, rather than CamelCase. This is
different from PySpark's design. For example, pandas API on Spark has
`to_pandas()`, whereas PySpark has `toPandas()` for converting a DataFrame into
a pandas DataFrame. In limited cases, to maintain compatibility with Spark, we
also provide Spark's variant as an alias.
-
-- Pandas API on Spark respects to the largest extent the conventions of the
Python numerical ecosystem, and allows the use of NumPy types, etc. that can be
supported by Spark.
-
-- pandas-on-Spark docs' style and infrastructure simply follow rest of the
PyData projects'.
-
-Unify small data (pandas) API and big data (Spark) API, but pandas first
Review comment:
This is removed. Now pandas-on-Spark specific APIs are placed under
`DataFrame.pandas_on_spark`. PySpark APIs are placed under `DataFrame.spark`
for now. `DataFrame` mainly only hold pandas APIs only.
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